Abstract
Breast cancer is the most common nonskin malignancy affecting women. Currently, no simple, blood-based diagnostic test exists to complement radiological screening and increase sensitivity of detection. To screen plasma specimens and identify biomarkers that detect HER2-positive breast cancer, automated robotic sample processing followed by surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectroscopy was used. Multiple statistical algorithms were used to select biomarkers that segregate cancer patients versus controls and produced average CV rates ranging from 20% to 29%. A set of seven biomarkers were validated on an independent test data set and achieved the best error rate of 19.1%. A permutation test indicateded a p-value for CV error less than 0.002. Moreover, a ROC curve using these biomarkers achieved an area-under-the-curve value of 0.95 on an independent test data set. The marker responsible for most of the resolving power was identified as a fragment of Fibrinogen Alpha (FGA) encompassing residues 605-629. This marker was present at lower levels in cancer patients as compared to controls. The importance of this biomarker was validated in a longitudinal study comparing pre- and post-operative levels and was shown to revert to normal levels after surgery. This fragment may serve as a useful diagnostic and treatment-monitoring marker.
Original language | English (US) |
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Pages (from-to) | 2947-2955 |
Number of pages | 9 |
Journal | Journal of Proteome Research |
Volume | 5 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2006 |
Externally published | Yes |
Keywords
- Breast cancer
- Fibrinogen
- HER2
- Plasma
- Proteomics